Applied analytics with Azure Databricks using Databricks SQL & Machine Learning

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Session Details:
Azure Databricks has been around for a long time. Every year we get great new updates, features, and patches, that make data analytics faster, easier, and more efficient. This time around, we will look into the new features of Machine learning with Scala, Python, R, and Databricks SQL.

Using a given dataset (alert: covid dataset), we will walk through various notebooks, scripts, and SQL code, delivering the attendees an insightful journey into this data.

Speaker Bio:
Tomaž Kaštrun is a SQL Server developer and data scientist with more than 15 years of experience in business warehousing, development, ETL, database administration, and query tuning. He holds over 15 years of experience in data analysis, data mining, statistical research, and machine learning. He is a Microsoft Data Platform MVP, a blogger, author of many articles, several books, and a frequent community speaker. Tomaž is an avid coffee drinker who is passionate about fixed-gear bikes.

Host/s:
Mark Broadbent.
Mikael Wedham.

Originally recorded on 20th October 2021.
Video Production: Mark Broadbent 27th January 2022.

00:00 Introduction
03:06 What's new
15:50 Demo 1: Overview, Spark 3.0, Runtimes, Git integration
20:26 Demo 2: Auto ML, Model predictions, ML Flow
28:44 Demo 3: Orchestrate tasks, Delta Live tables, Delta Lake and Lakehouse
33:36 Demo 4: Databricks SQL
46:12 Summary
46:21 Questions

[HybridVirtualGroup]

Use the following timings to jump to your content of interest:
00:00 Introduction
03:06 What's new
15:50 Demo 1: Overview, Spark 3.0, Runtimes, Git integration
20:26 Demo 2: Auto ML, Model predictions, ML Flow
28:44 Demo 3: Orchestrate tasks, Delta Live tables, Delta Lake and Lakehouse
33:36 Demo 4: Databricks SQL
46:12 Summary
46:21 Questions